DNAJB1-PRKACA fusion neoantigens elicit rare endogenous T cell responses that potentiate cell therapy for fibrolamellar carcinoma.

Fibrolamellar carcinoma (FLC) is a liver tumor with a high mortality burden and few treatment options. A promising therapeutic vulnerability in FLC is its driver mutation, a conserved DNAJB1-PRKACA gene fusion that could be an ideal target neoantigen for immunotherapy. In this study, we aim to define endogenous CD8 T cell responses to this fusion in FLC patients and evaluate fusion-specific T cell receptors (TCRs) for use in cellular immunotherapies. We observe that fusion-specific CD8 T cells are rare and that FLC patient TCR repertoires lack large clusters of related TCR sequences characteristic of potent antigen-specific responses, potentially explaining why endogenous immune responses are insufficient to clear FLC tumors. Nevertheless, we define two functional fusion-specific TCRs, one of which has strong anti-tumor activity in vivo. Together, our results provide insights into the fragmented nature of neoantigen-specific repertoires in humans and indicate routes for clinical development of successful immunotherapies for FLC.

MHCpLogics: an interactive machine learning-based tool for unsupervised data visualization and cluster analysis of immunopeptidomes.

The major histocompatibility complex (MHC) encodes a range of immune response genes, including the human leukocyte antigens (HLAs) in humans. These molecules bind peptide antigens and present them on the cell surface for T cell recognition. The repertoires of peptides presented by HLA molecules are termed immunopeptidomes. The highly polymorphic nature of the genres that encode the HLA molecules confers allotype-specific differences in the sequences of bound ligands. Allotype-specific ligand preferences are often defined by peptide-binding motifs. Individuals express up to six classical class I HLA allotypes, which likely present peptides displaying different binding motifs. Such complex datasets make the deconvolution of immunopeptidomic data into allotype-specific contributions and further dissection of binding-specificities challenging. Herein, we developed MHCpLogics as an interactive machine learning-based tool for mining peptide-binding sequence motifs and visualization of immunopeptidome data across complex datasets. We showcase the functionalities of MHCpLogics by analyzing both in-house and published mono- and multi-allelic immunopeptidomics data. The visualization modalities of MHCpLogics allow users to inspect clustered sequences down to individual peptide components and to examine broader sequence patterns within multiple immunopeptidome datasets. MHCpLogics can deconvolute large immunopeptidome datasets enabling the interrogation of clusters for the segregation of allotype-specific peptide sequence motifs, identification of sub-peptidome motifs, and the exportation of clustered peptide sequence lists. The tool facilitates rapid inspection of immunopeptidomes as a resource for the immunology and vaccine communities. MHCpLogics is a standalone application available via an executable installation at: https://github.com/PurcellLab/MHCpLogics.

Profound N-glycan remodelling accompanies MHC-II immunopeptide presentation.

Immunopeptidomics, the study of peptide antigens presented on the cell surface by the major histocompatibility complex (MHC), offers insights into how our immune system recognises self/non-self in health and disease. We recently discovered that hyper-processed (remodelled) N-glycans are dominant features decorating viral spike immunopeptides presented via MHC-class II (MHC-II) molecules by dendritic cells pulsed with SARS-CoV-2 spike protein, but it remains unknown if endogenous immunopeptides also undergo N-glycan remodelling. Taking a multi-omics approach, we here interrogate published MHC-II immunopeptidomics datasets of cultured monocyte-like (THP-1) and breast cancer-derived (MDA-MB-231) cell lines for overlooked N-glycosylated peptide antigens, which we compare to their source proteins in the cellular glycoproteome using proteomics and N-glycomics data from matching cell lines. Hyper-processed chitobiose core and paucimannosidic N-glycans alongside under-processed oligomannosidic N-glycans were found to prevalently modify MHC-II-bound immunopeptides isolated from both THP-1 and MDA-MB-231, while complex/hybrid-type N-glycans were (near-)absent in the immunopeptidome as supported further by new N-glycomics data generated from isolated MHC-II-bound peptides derived from MDA-MB-231 cells. Contrastingly, the cellular proteomics and N-glycomics data from both cell lines revealed conventional N-glycosylation rich in complex/hybrid-type N-glycans, which, together with the identification of key lysosomal glycosidases, suggest that MHC-II peptide antigen processing is accompanied by extensive N-glycan trimming. N-glycan remodelling appeared particularly dramatic for cell surface-located glycoproteins while less remodelling was observed for lysosomal-resident glycoproteins. Collectively, our findings indicate that both under- and hyper-processed N-glycans are prevalent features of endogenous MHC-II immunopeptides, an observation that demands further investigation to enable a better molecular-level understanding of immune surveillance.

Endogenous H3.3K27M derived peptide restricted to HLA-A∗02:01 is insufficient for immune-targeting in diffuse midline glioma.

Diffuse midline glioma (DMG) is a childhood brain tumor with an extremely poor prognosis. Chimeric antigen receptor (CAR) T cell therapy has recently demonstrated some success in DMG, but there may a need to target multiple tumor-specific targets to avoid antigen escape. We developed a second-generation CAR targeting an HLA-A∗02:01 restricted histone 3K27M epitope in DMG, the target of previous peptide vaccination and T cell receptor-mimics. These CAR T cells demonstrated specific, titratable, binding to cells pulsed with the H3.3K27M peptide. However, we were unable to observe scFv binding, CAR T cell activation, or cytotoxic function against H3.3K27M+ patient-derived models. Despite using sensitive immunopeptidomics, we could not detect the H3.3K27M26-35-HLA-A∗02:01 peptide on these patient-derived models. Interestingly, other non-mutated peptides from DMG were detected bound to HLA-A∗02:01 and other class I molecules, including a novel HLA-A3-restricted peptide encompassing the K27M mutation and overlapping with the H3 K27M26-35-HLA-A∗02:01 peptide. These results suggest that targeting the H3 K27M26-35 mutation in context of HLA-A∗02:01 may not be a feasible immunotherapy strategy because of its lack of presentation. These findings should inform future investigations and clinical trials in DMG.

A combined immunopeptidomics, proteomics, and cell surface proteomics approach to identify immunotherapy targets for diffuse intrinsic pontine glioma.

Introduction: Diffuse intrinsic pontine glioma (DIPG), recently reclassified as a subtype of diffuse midline glioma, is a highly aggressive brainstem tumor affecting children and young adults, with no cure and a median survival of only 9 months. Conventional treatments are ineffective, highlighting the need for alternative therapeutic strategies such as cellular immunotherapy. However, identifying unique and tumor-specific cell surface antigens to target with chimeric antigen receptor (CAR) or T-cell receptor (TCR) therapies is challenging. Methods: In this study, a multi-omics approach was used to interrogate patient-derived DIPG cell lines and to identify potential targets for immunotherapy. Results: Through immunopeptidomics, a range of targetable peptide antigens from cancer testis and tumor-associated antigens as well as peptides derived from human endogenous retroviral elements were identified. Proteomics analysis also revealed upregulation of potential drug targets and cell surface proteins such as Cluster of differentiation 27 (CD276) B7 homolog 3 protein (B7H3), Interleukin 13 alpha receptor 2 (IL-13Rα2), Human Epidermal Growth Factor Receptor 3 (HER2), Ephrin Type-A Receptor 2 (EphA2), and Ephrin Type-A Receptor 3 (EphA3). Discussion: The results of this study provide a valuable resource for the scientific community to accelerate immunotherapeutic approaches for DIPG. Identifying potential targets for CAR and TCR therapies could open up new avenues for treating this devastating disease.

The allopurinol metabolite, oxypurinol, drives oligoclonal expansions of drug-reactive T cells in resolved hypersensitivity cases and drug-naïve healthy donors.

Allopurinol (ALP) is a successful drug used in the treatment of gout. However, this drug has been implicated in hypersensitivity reactions that can cause severe to life-threatening reactions such as Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN). Individuals who carry the human leukocyte antigen (HLA)-B*58:01 allotype are at higher risk of experiencing a hypersensitivity reaction (odds ratios ranging from 5.62 to 580.3 for mild to severe reactions, respectively). In addition to the parent drug, the metabolite oxypurinol (OXP) is implicated in triggering T cell-mediated immunopathology via a labile interaction with HLA-B*58:01. To date, there has been limited information regarding the T-cell receptor (TCR) repertoire usage of reactive T cells in patients with ALP-induced SJS or TEN and, in particular, there are no reports examining paired αßTCRs. Here, using in vitro drug-treated PBMCs isolated from both resolved ALP-induced SJS/TEN cases and drug-naïve healthy donors, we show that OXP is the driver of CD8+ T cell-mediated responses and that drug-exposed memory T cells can exhibit a proinflammatory immunophenotype similar to T cells described during active disease. Furthermore, this response supported the pharmacological interaction with immune receptors (p-i) concept by showcasing (i) the labile metabolite interaction with peptide/HLA complexes, (ii) immunogenic complex formation at the cell surface, and (iii) lack of requirement for antigen processing to elicit drug-induced T cell responsiveness. Examination of paired OXP-induced αßTCR repertoires highlighted an oligoclonal and private clonotypic profile in both resolved ALP-induced SJS/TEN cases and drug-naïve healthy donors.

Complimentary electrostatics dominate T-cell receptor binding to a psoriasis-associated peptide antigen presented by human leukocyte antigen C∗06:02.

Psoriasis is a chronic skin disease characterized by hyperproliferative epidermal lesions infiltrated by autoreactive T cells. Individuals expressing the human leukocyte antigen (HLA) C∗06:02 allele are at highest risk for developing psoriasis. An autoreactive T cell clone (termed Vα3S1/Vß13S1) isolated from psoriatic plaques is selective for HLA-C∗06:02, presenting a peptide derived from the melanocyte-specific autoantigen ADAMTSL5 (VRSRRCLRL). Here we determine the crystal structure of this psoriatic TCR-HLA-C∗06:02 ADAMTSL5 complex with a stabilized peptide. Docking of the TCR involves an extensive complementary charge network formed between negatively charged TCR residues interleaving with exposed arginine residues from the self-peptide and the HLA-C∗06:02 α1 helix. We probed these interactions through mutagenesis and activation assays. The charged interface spans the polymorphic region of the C1/C2 HLA group. Notably the peptide-binding groove of HLA-C∗06:02 appears exquisitely suited for presenting highly charged Arg-rich epitopes recognized by this acidic psoriatic TCR. Overall, we provide a structural basis for understanding the engagement of melanocyte antigen-presenting cells by a TCR implicated in psoriasis while simultaneously expanding our knowledge of how TCRs engage HLA-C.

SAPrIm, a semi-automated protocol for mid-throughput immunopeptidomics.

Human leukocyte antigen (HLA) molecules play a crucial role in directing adaptive immune responses based on the nature of their peptide ligands, collectively coined the immunopeptidome. As such, the study of HLA molecules has been of major interest in the development of cancer immunotherapies such as vaccines and T-cell therapies. Hence, a comprehensive understanding and profiling of the immunopeptidome is required to foster the growth of these personalised solutions. We herein describe SAPrIm, an Immunopeptidomics tool for the Mid-Throughput era. This is a semi-automated workflow involving the KingFisher platform to isolate immunopeptidomes using anti-HLA antibodies coupled to a hyper-porous magnetic protein A microbead, a variable window data independent acquisition (DIA) method and the ability to run up to 12 samples in parallel. Using this workflow, we were able to concordantly identify and quantify ~400 - 13000 unique peptides from 5e5 - 5e7 cells, respectively. Overall, we propose that the application of this workflow will be crucial for the future of immunopeptidome profiling, especially for mid-size cohorts and comparative immunopeptidomics studies.

Benchmarking Bioinformatics Pipelines in Data-Independent Acquisition Mass Spectrometry for Immunopeptidomics.

Immunopeptidomes are the peptide repertoires bound by the molecules encoded by the major histocompatibility complex [human leukocyte antigen (HLA) in humans]. These HLA-peptide complexes are presented on the cell surface for immune T-cell recognition. Immunopeptidomics denotes the utilization of tandem mass spectrometry to identify and quantify peptides bound to HLA molecules. Data-independent acquisition (DIA) has emerged as a powerful strategy for quantitative proteomics and deep proteome-wide identification; however, DIA application to immunopeptidomics analyses has so far seen limited use. Further, of the many DIA data processing tools currently available, there is no consensus in the immunopeptidomics community on the most appropriate pipeline(s) for in-depth and accurate HLA peptide identification. Herein, we benchmarked four commonly used spectral library-based DIA pipelines developed for proteomics applications (Skyline, Spectronaut, DIA-NN, and PEAKS) for their ability to perform immunopeptidome quantification. We validated and assessed the capability of each tool to identify and quantify HLA-bound peptides. Generally, DIA-NN and PEAKS provided higher immunopeptidome coverage with more reproducible results. Skyline and Spectronaut conferred more accurate peptide identification with lower experimental false-positive rates. All tools demonstrated reasonable correlations in quantifying precursors of HLA-bound peptides. Our benchmarking study suggests a combined strategy of applying at least two complementary DIA software tools to achieve the greatest degree of confidence and in-depth coverage of immunopeptidome data.

Screening self-peptides for recognition by mouse alloreactive CD8+ T cells using direct ex vivo multimer staining.

Here, we present a protocol to identify immunogenic self-peptide/allogeneic major histocompatibility complex (MHC) epitopes. We describe the generation of enriched alloreactive CD8+ T cells by priming mice with a skin graft expressing the allogeneic MHC class I molecule of interest, followed by boosting with a liver-specific AAV vector encoding the heavy chain of that donor MHC allomorph. We then use a peptide-exchange approach to assemble a range of peptide-MHC (pMHC) multimers for measuring recognition of the various epitopes by these alloreactive T cells. For complete details on the use and execution of this protocol, please refer to Son et al. (2021).1.

Understanding the Role of HLA Class I Molecules in the Immune Response to Influenza Infection and Rational Design of a Peptide-Based Vaccine.

Influenza A virus is a respiratory pathogen that is responsible for regular epidemics and occasional pandemics that result in substantial damage to life and the economy. The yearly reformulation of trivalent or quadrivalent flu vaccines encompassing surface glycoproteins derived from the current circulating strains of the virus does not provide sufficient cross-protection against mismatched strains. Unlike the current vaccines that elicit a predominant humoral response, vaccines that induce CD8+ T cells have demonstrated a capacity to provide cross-protection against different influenza strains, including novel influenza viruses. Immunopeptidomics, the mass spectrometric identification of human-leukocyte-antigen (HLA)-bound peptides isolated from infected cells, has recently provided key insights into viral peptides that can serve as potential T cell epitopes. The critical elements required for a strong and long-living CD8+ T cell response are related to both HLA restriction and the immunogenicity of the viral peptide. This review examines the importance of HLA and the viral immunopeptidome for the design of a universal influenza T-cell-based vaccine.

Multi-Omic Analysis of Two Common P53 Mutations: Proteins Regulated by Mutated P53 as Potential Targets for Immunotherapy.

The p53 protein is mutated in more than 50% of human cancers. Mutated p53 proteins not only lose their normal function but often acquire novel oncogenic functions, a phenomenon termed mutant p53 gain-of-function. Mutant p53 has been shown to affect the transcription of a range of genes, as well as protein-protein interactions with transcription factors and other effectors; however, no one has intensively investigated and identified these proteins, or their MHC presented epitopes, from the viewpoint of their ability to act as targets for immunotherapeutic interventions. We investigated the molecular changes that occurred after the TP53 null osteosarcoma cells, SaOS-2, were transfected with one of two conformational p53-mutants, either R175H or R273H. We then examined the phenotypic and functional changes using macroscopic observations, proliferation, gene expression and proteomics alongside immunopeptidome profiling of peptide antigen presentation in the context of major histocompatibility complex (MHC) class I molecules. We identified several candidate proteins in both TP53 mutant cell lines with differential expression when compared to the TP53 null vector control, SaOS-V. Quantitative SWATH proteomics combined with immune-peptidome analysis of the class-I eluted peptides identified several epitopes presented on pMHC and in silico analysis shortlisted which antigens were expressed in a range of cancerous but not adjacent healthy tissues. Out of all the candidates, KLC1 and TOP2A showed high levels of expression in every tumor type examined. From these proteins, three A2 and four pan HLA-A epitopes were identified in both R175H and R273H from TOP2A. We have now provided a short list of future immunotherapy targets for the treatment of cancers harboring mutated TP53.

New insights and approaches for analyses of immunopeptidomes.

Human leucocyte antigen (HLA) molecules play a key role in health and disease by presenting antigen to T-lymphocytes for immunosurveillance. Immunopeptidomics involves the study of the collection of peptides presented within the antigen-binding groove of HLA molecules. Identifying their nature and diversity is crucial to understanding immunosurveillance especially during infection or for the recognition and potential eradication of tumours. This review discusses recent advances in the isolation, identification, and quantitation of these peptide antigens. New informatics approaches and databases have shed light on the extent of peptide antigens derived from unconventional sources including peptides derived from transcripts associated with frame shifts, long noncoding RNA, incorrectly annotated untranslated regions, post-translational modifications, and proteasomal splicing. Several challenges remain in successful analysis of immunopeptides, yet recent developments point to unexplored biology waiting to be unravelled.

Defective Proinsulin Handling Modulates the MHC I Bound Peptidome and Activates the Inflammasome in ß-Cells.

How immune tolerance is lost to pancreatic ß-cell peptides triggering autoimmune type 1 diabetes is enigmatic. We have shown that loss of the proinsulin chaperone glucose-regulated protein (GRP) 94 from the endoplasmic reticulum (ER) leads to mishandling of proinsulin, ER stress, and activation of the immunoproteasome. We hypothesize that inadequate ER proinsulin folding capacity relative to biosynthetic need may lead to an altered ß-cell major histocompatibility complex (MHC) class-I bound peptidome and inflammasome activation, sensitizing ß-cells to immune attack. We used INS-1E cells with or without GRP94 knockout (KO), or in the presence or absence of GRP94 inhibitor PU-WS13 (GRP94i, 20 µM), or exposed to proinflammatory cytokines interleukin (IL)-1ß or interferon gamma (IFNγ) (15 pg/mL and 10 ng/mL, respectively) for 24 h. RT1.A (rat MHC I) expression was evaluated using flow cytometry. The total RT1.A-bound peptidome analysis was performed on cell lysates fractionated by reverse-phase high-performance liquid chromatography (RP-HPLC), followed by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). The nucleotide-binding oligomerization domain, leucine rich repeat and pyrin domain containing protein (NLRP1), nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor alpha (IκBα), and (pro) IL-1ß expression and secretion were investigated by Western blotting. GRP94 KO increased RT1.A expression in ß-cells, as did cytokine exposure compared to relevant controls. Immunopeptidome analysis showed increased RT1.A-bound peptide repertoire in GRP94 KO/i cells as well as in the cells exposed to cytokines. The GRP94 KO/cytokine exposure groups showed partial overlap in their peptide repertoire. Notably, proinsulin-derived peptide diversity increased among the total RT1.A peptidome in GRP94 KO/i along with cytokines exposure. NLRP1 expression was upregulated in GRP94 deficient cells along with decreased IκBα content while proIL-1ß cellular levels declined, coupled with increased secretion of mature IL-1ß. Our results suggest that limiting ß-cell proinsulin chaperoning enhances RT1.A expression alters the MHC-I peptidome including proinsulin peptides and activates inflammatory pathways, suggesting that stress associated with impeding proinsulin handling may sensitize ß-cells to immune-attack.

HLA-A*11:01-restricted CD8+ T cell immunity against influenza A and influenza B viruses in Indigenous and non-Indigenous people.

HLA-A*11:01 is one of the most prevalent human leukocyte antigens (HLAs), especially in East Asian and Oceanian populations. It is also highly expressed in Indigenous people who are at high risk of severe influenza disease. As CD8+ T cells can provide broadly cross-reactive immunity to distinct influenza strains and subtypes, including influenza A, B and C viruses, understanding CD8+ T cell immunity to influenza viruses across prominent HLA types is needed to rationally design a universal influenza vaccine and generate protective immunity especially for high-risk populations. As only a handful of HLA-A*11:01-restricted CD8+ T cell epitopes have been described for influenza A viruses (IAVs) and epitopes for influenza B viruses (IBVs) were still unknown, we embarked on an epitope discovery study to define a CD8+ T cell landscape for HLA-A*11:01-expressing Indigenous and non-Indigenous Australian people. Using mass-spectrometry, we identified IAV- and IBV-derived peptides presented by HLA-A*11:01 during infection. 79 IAV and 57 IBV peptides were subsequently screened for immunogenicity in vitro with peripheral blood mononuclear cells from HLA-A*11:01-expressing Indigenous and non-Indigenous Australian donors. CD8+ T cell immunogenicity screening revealed two immunogenic IAV epitopes (A11/PB2320-331 and A11/PB2323-331) and the first HLA-A*11:01-restricted IBV epitopes (A11/M41-49, A11/NS1186-195 and A11/NP511-520). The immunogenic IAV- and IBV-derived peptides were >90% conserved among their respective influenza viruses. Identification of novel immunogenic HLA-A*11:01-restricted CD8+ T cell epitopes has implications for understanding how CD8+ T cell immunity is generated towards IAVs and IBVs. These findings can inform the development of rationally designed, broadly cross-reactive influenza vaccines to ensure protection from severe influenza disease in HLA-A*11:01-expressing individuals.

MhcVizPipe: A Quality Control Software for Rapid Assessment of Small- to Large-Scale Immunopeptidome Datasets.

MS-based immunopeptidomics is maturing into an automatized and high-throughput technology, producing small- to large-scale datasets of clinically relevant major histocompatibility complex (MHC) class I-associated and class II-associated peptides. Consequently, the development of quality control (QC) and quality assurance systems capable of detecting sample and/or measurement issues is important for instrument operators and scientists in charge of downstream data interpretation. Here, we created MhcVizPipe (MVP), a semiautomated QC software tool that enables rapid and simultaneous assessment of multiple MHC class I and II immunopeptidomic datasets generated by MS, including datasets generated from large sample cohorts. In essence, MVP provides a rapid and consolidated view of sample quality, composition, and MHC specificity to greatly accelerate the "pass-fail" QC decision-making process toward data interpretation. MVP parallelizes the use of well-established immunopeptidomic algorithms (NetMHCpan, NetMHCIIpan, and GibbsCluster) and rapidly generates organized and easy-to-understand reports in HTML format. The reports are fully portable and can be viewed on any computer with a modern web browser. MVP is intuitive to use and will find utility in any specialized immunopeptidomic laboratory and proteomics core facility that provides immunopeptidomic services to the community.

The differentiation state of the Schwann cell progenitor drives phenotypic variation between two contagious cancers.

Contagious cancers are a rare pathogenic phenomenon in which cancer cells gain the ability to spread between genetically distinct hosts. Nine examples have been identified across marine bivalves, dogs and Tasmanian devils, but the Tasmanian devil is the only mammalian species known to have given rise to two distinct lineages of contagious cancer, termed Devil Facial Tumour 1 (DFT1) and 2 (DFT2). Remarkably, DFT1 and DFT2 arose independently from the same cell type, a Schwann cell, and while their ultra-structural features are highly similar they exhibit variation in their mutational signatures and infection dynamics. As such, DFT1 and DFT2 provide a unique framework for investigating how a common progenitor cell can give rise to distinct contagious cancers. Using a proteomics approach, we show that DFT1 and DFT2 are derived from Schwann cells in different differentiation states, with DFT2 carrying a molecular signature of a less well differentiated Schwann cell. Under inflammatory signals DFT1 and DFT2 have different gene expression profiles, most notably involving Schwann cell markers of differentiation, reflecting the influence of their distinct origins. Further, DFT2 cells express immune cell markers typically expressed during nerve repair, consistent with an ability to manipulate their extracellular environment, facilitating the cell's ability to transmit between individuals. The emergence of two contagious cancers in the Tasmanian devil suggests that the inherent plasticity of Schwann cells confers a vulnerability to the formation of contagious cancers.

RHybridFinder: An R package to process immunopeptidomic data for putative hybrid peptide discovery.

Identification of proteasomal spliced peptides (PSPs) by mass spectrometry (MS) is not possible with traditional search engines. Here, we provide a protocol for running RHybridFinder (RHF), an R package for the computational inference of putative PSPs detected by MS. RHF extracts high confidence scored de novo sequenced peptides identified by PEAKS software. Those peptides are then matched to protein databases to infer cis- or trans-spliced major histocompatibility complex (MHC)-associated peptides. RHF is relatively fast and straightforward. PSPs have to be validated experimentally. For complete details on the use and execution of the original protocol, please refer to Faridi et al. (2018).

Immunopeptidogenomics: Harnessing RNA-Seq to Illuminate the Dark Immunopeptidome.

Human leukocyte antigen (HLA) molecules are cell-surface glycoproteins that present peptide antigens on the cell surface for surveillance by T lymphocytes, which contemporaneously seek signs of disease. Mass spectrometric analysis allows us to identify large numbers of these peptides (the immunopeptidome) following affinity purification of solubilized HLA-peptide complexes. However, in recent years, there has been a growing awareness of the "dark side" of the immunopeptidome: unconventional peptide epitopes, including neoepitopes, which elude detection by conventional search methods because their sequences are not present in reference protein databases (DBs). Here, we establish a bioinformatics workflow to aid identification of peptides generated by noncanonical translation of mRNA or by genome variants. The workflow incorporates both standard transcriptomics software and novel computer programs to produce cell line-specific protein DBs based on three-frame translation of the transcriptome. The final protein DB also includes sequences resulting from variants determined by variant calling on the same RNA-Seq data. We then searched our experimental data against both transcriptome-based and standard DBs using PEAKS Studio (Bioinformatics Solutions, Inc). Finally, further novel software helps to compare the various result sets arising for each sample, pinpoint putative genomic origins for unconventional sequences, and highlight potential neoepitopes. We applied the workflow to study the immunopeptidome of the acute myeloid leukemia cell line THP-1, using RNA-Seq and immunopeptidome data. We confidently identified over 14,000 peptides from three replicates of purified HLA peptides derived from THP-1 cells using the conventional UniProt human proteome. Using the transcriptome-based DB generated using our workflow, we recapitulated >85% of these and also identified 1029 unconventional peptides not explained by UniProt, including 16 sequences caused by nonsynonymous variants. Our workflow, which we term "immunopeptidogenomics," can provide DBs, which include pertinent unconventional sequences and allow neoepitope discovery, without becoming too large to search. Immunopeptidogenomics is a step toward unbiased search approaches that are needed to illuminate the dark side of the immunopeptidome.